Hierarchical Roadmap Approach to Rough Terrain Motion Planning

Michael Brunner, Bernd Brüggemann, Dirk Schulz

Abstract

A reconfigurable chassis provides a mobile robot with a high degree of mobility and enables it to overcome rough terrain in unstructured outdoor environments, like boulders or rubble, and challenging structures in urban environments, like stairs or steps. Yet, many planning algorithms rarely exploit those enhanced capabilities to the full extent, limiting these systems to mainly flat environments also traversable by less capable fixed-chassis robots. In this paper we introduce a two-stage roadmap approach to motion planning for reconfigurable robots which utilizes the system's actuators to traverse rough terrain and obstacles. First, by considering the platform's operating limits rather than the complete state, we quickly generate an initial path. Second, we refine the initial path in rough areas within a constrained search space. So we are able to plan appropriate actuator configurations to traverse rough areas and ensure the system's safety. Our algorithm does not categorize the terrain and does not use any predefined motion sequences. Hence, our planner can be applied to urban structures, like stairs, as well as rough unstructured environments. We present simulation experiments to provide more insight into our method and real-world experiments to prove the feasibility of our motion planning approach on a real robot.

References

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Paper Citation


in Harvard Style

Brunner M., Brüggemann B. and Schulz D. (2013). Hierarchical Roadmap Approach to Rough Terrain Motion Planning . In Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8565-38-9, pages 35-46. DOI: 10.5220/0004229000350046


in Bibtex Style

@conference{icaart13,
author={Michael Brunner and Bernd Brüggemann and Dirk Schulz},
title={Hierarchical Roadmap Approach to Rough Terrain Motion Planning},
booktitle={Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2013},
pages={35-46},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004229000350046},
isbn={978-989-8565-38-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Hierarchical Roadmap Approach to Rough Terrain Motion Planning
SN - 978-989-8565-38-9
AU - Brunner M.
AU - Brüggemann B.
AU - Schulz D.
PY - 2013
SP - 35
EP - 46
DO - 10.5220/0004229000350046